The preference-based data collection and discounting system and methods herein collect consumer product preferences and track the buying habits of a consumer and reward consumers through discounts. The buying habits may be interrogated by a database of one or more algorithms, which will result in a collated database about consumer buying habits. This metadata may be used by vendors to make marketing assumptions that will influence a consumer's future purchase decisions. Consumers directly input and update their preferences as well.
Legal claims defining the scope of protection, as filed with the USPTO.
1. A method for preference-based data collection and discounting comprising: providing, by one or more processors, a consumer unique identifier; receiving, by the one or more processors, a list of products associated with the consumer unique identifier, wherein the order of the list of more than one product is identified; calculating, by the one or more processors, a discount multiplier for each product in the list of products, wherein the discount multiplier is based on the position of each product in the list of products; receiving, by the one or more processors, confirmation of the consumer unique identifier accessed at a transaction; accessing, by the one or more processors, the list of products associated with the identified consumer unique identifier; determining, by the one or more processors, if one of the products of the transaction are present on the list of products; applying, by the one or more processors, the discount multiplier to each individual product of the transaction based on the product's position on the list of products; modifying, by the one or more processors, the price of the transaction based on the applied discount multiplier; and updating, by the one or more processors, the list of products based on the specific products involved in the transaction by recalculating the discount multiplier for each product on the list based on an updated specific order.
2. The method of claim 1 , further comprising, monitoring, by one or more processors, the list of products to determine if an alteration to the ordering of the list of products occurs.
3. The method of claim 1 , further comprising, reordering, by one or more processors, the products on the list of products when a transaction is completed, wherein products involved in the transaction are removed from the list of products and the products remaining on the list of products are adjusted sequentially.
4. The method of claim 1 , wherein, a logistic regression is applied to the list of products to determine the discount multiplier.
5. The method of claim 1 , wherein the discount multiplier is calculated, by one or more processors, based on a predetermined equation associated with the position on the list of products.
6. The method of claim 5 , wherein, the predetermined equation is either quadratic or linear.
7. The method of claim 1 , wherein the discount multiplier may further comprise, calculating, by one or more processors, a variable based on a regression calculation for a predetermined number of positions on the list of products.
8. The method of claim 7 , wherein the regression calculation is linear or quadratic.
9. A computer program product for preference-based data collection and discounting, the computer program product comprising: one or more non-transitory computer readable storage media and program instructions stored on the one or more computer readable storage media, the program instructions executed by a processor to perform tasks comprising: provide a consumer unique identifier; receive a list of products associated with the consumer unique identifier, wherein the order of the list of more than one product is identified; calculate a discount multiplier for each product in the list of products, wherein the discount multiplier is based on the position of each product in the list of products; receive confirmation of the consumer unique identifier accessed at a transaction; access the list of products associated with the identified consumer unique identifier; determine if one of the products of the transaction are present on the list of products; apply the discount multiplier to each individual product of the transaction based on the product's position on the list of products; modify the price of the transaction based on the applied discount multiplier; and update the list of products based on the specific products involved in the transaction by recalculating the discount multiplier for each product on the list based on an updated specific order.
10. The computer program product of claim 9 , further comprising, program instructions to monitor the list of products to determine if an alteration to the ordering of the list of products occurs.
11. The computer program product of 9 , further comprising, program instructions to reorder the products on the list of products when a transaction is completed, wherein products involved in the transaction are removed from the list of products and the products remaining on the list of products are adjusted sequentially.
12. The computer program product of claim 9 , wherein, a logistic regression is applied to the list of products to determine the discount multiplier.
13. The computer program product of claim 9 , wherein program instructions calculated the discount multiplier based on a predetermined equation associated with the position on the list of products.
14. The computer program product of claim 13 , wherein, the predetermined equation is either quadratic or linear.
15. The computer program product of claim 9 , wherein program instructions calculate a variable based on a regression calculation for a predetermined number of positions on the list of products for the discount multiplier.
16. The computer program product of claim 15 , wherein the regression calculation is linear, or quadratic based on the regression calculation.
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August 13, 2018
June 18, 2019
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